Function to check cat2cat ml models performance

ml and mappings arguments in cat2cat function can be used to run cross validation across all groups in ml data.

cat2cat_ml_run(mappings, ml, ...)

# S3 method for cat2cat_ml_run
print(x, ...)

Arguments

mappings

`named list` with 3 fields `trans`, `direction` and optional `freqs_df`.

ml

`named list` (optional) with up to 5 fields `data`, `cat_var`, `method`, `features` and optional `args`.

...

other arguments

x

cat2cat_ml_run instance created with cat2cat_ml_run function.

Value

argument x invisibly

See also

cat2cat

Examples

if (FALSE) {
library("cat2cat")
data("occup", package = "cat2cat")
data("trans", package = "cat2cat")

occup_2006 <- occup[occup$year == 2006, ]
occup_2008 <- occup[occup$year == 2008, ]
occup_2010 <- occup[occup$year == 2010, ]
occup_2012 <- occup[occup$year == 2012, ]

library("caret")
ml_setup <- list(
  data = rbind(occup_2010, occup_2012),
  cat_var = "code",
  method = c("knn", "rf", "lda"),
  features = c("age", "sex", "edu", "exp", "parttime", "salary"),
  args = list(k = 10, ntree = 50)
)
data <- list(
  old = occup_2008, new = occup_2010,
  cat_var_old = "code", cat_var_new = "code", time_var = "year"
)
mappings <- list(trans = trans, direction = "backward")
res <- cat2cat_ml_run(mappings, ml_setup, test_prop = 0.2)
res
}